WO2009030364A1

WO2009030364A1 - Method and system for the optimised planning of complex production sequences in the industrial operation of installations

Info

Publication number: WO2009030364A1
Application number: PCT/EP2008/006820
Authority: WO
Inventors: Iiro Harjunkoski
Original assignee: Abb Research Ltd.
Priority date: 2007-08-31
Filing date: 2008-08-20
Publication date: 2009-03-12
Also published as: CN101790746A; DE102007041424A1; BRPI0816060A2; JP5341090B2; JP2010537328A; EP2195779A1

Abstract

The invention relates to a method and a system for the optimised planning of complex production sequences in the industrial operation of installations, especially in the steel industry, by the programming-related use of a mixed integer optimisation method based on methods and algorithms of the Mixed Integer Linear Programming (MILP). Taking into account pre-determined rules, product characteristics, operating means characteristics, products to be produced are grouped and sequenced into product families and product groups in an optimised manner, in stages, and an optimised product sequence or production sequence is determined.

Description

METHOD AND SYSTEM FOR THE OPTIMIZED PLANNING OF COMPLEX PRODUCTION SUBSEQUENCES IN LARGE-SCALE PLANT ENGINEERING

description

The invention relates to a method for the optimized planning of complex production sequences in large-scale plant operations, in particular in the steel industry, the metalworking industry, the pharmaceutical and / or the chemical industry using program-technically implemented mixed-integer optimization method.

Furthermore, the invention also includes a corresponding system for carrying out the method.

Due to the immense quantity or quantity of products to be manufactured and the unbelievable amount or mass of starting materials and complexity of the processes to avoid economic damage, for example due to unwanted downtime of the plant operation, especially due to conversion work and / or cleaning during a product change , special planning-technical efforts to ensure a smooth and uninterrupted manufacturing process or plant operation required.

The above applies in particular in the steel industry, where, by suitable selection of the sequence of the individual slabs or steel blanks, which differ essentially in terms of their geometric dimensions and steel quality, a continuous casting process of the steel and / or iron blanks to be processed is to be effected. is guaranteed. The same applies to the further processing of the blanks produced by means of rolling mills but also in the chemical / pharmaceutical industry and / or the pulp and paper industry application. Here again, in order to ensure the most efficient production process possible, a product or production sequence which is optimized according to demand or specification, for example sheets, must be adhered to. The specification data may include physical, chemical and / or geometric properties, such as thickness, length, width, density, structure, elasticity, hardness, chemical composition.

One known approach to determining the product sequence in steelmaking is given in the article by Grossman and Harjunkoski, "A decomposition approach for the scheduling of a steel plant production" (Computers and Chemical Engineering, 25, 2001, pages 1647-1660) The aim is to increase the efficiency of the production plant by extending or expanding the continuous casting sequences, which means a reduction in downtime or downtime in steelmaking or steelmaking. For example, delivery date, width, quality and thickness were achieved by combining blanks of the same quality and thickness into a product family, forming corresponding casting sequences within a product family a uniform or decreasing width of the steel blanks from the previous to the following blank was a prerequisite.

The invention has for its object a possibility for improved planning of complex production sequences in large-scale plant operations, such as from the steel, pharmaceutical and / or chemical industries specify.

The aforementioned object is achieved by a method and a system of the aforementioned type with the features of the independent claims. Advantageous embodiments tions of the invention are given in the following description and in the dependent claims.

According to the method for optimizing planning of complex production sequences in large-scale plant operations, in particular the steel and / or pulp and / or paper and / or chemical / pharmaceutical industry, by programmatic application of a method and algorithms of Mixed Integer Linear Programming (MILP) constructive, mixed-integer optimization method and under processing and / or incorporation of predetermined rules and product characteristics but also of resource characteristics step by step carried out an order-dependent optimized grouping and optimized sequencing products to be produced and determined as an optimized product sequence or production sequence.

For this purpose, in a first step, depending on product characteristics, such as delivery date, length, width, thickness, height, weight, density, quality, quality, purity, strength, elasticity and chemical composition of the respective product, as well as by equipment characteristics, which, for example Availability, Condition, Throughput, Consumption, Achievable Quality and / or Production Speed, Utilization, Capacities Dependencies and / or shortcuts of equipment, operating, standstill and / or maintenance information and times, product and / or process paths and times, especially Pass or cycle times, may relate, and / or other predetermined rules, which are in particular determined by the manufacturing process, carried out a sequential pre-sorting of the products to be produced.

The aforementioned rules essentially take into account geometric, chemical and / or physical requirements and / or limitations of the respective manufacturing process and / or the plant operation used for product production. Geometric rules take significant account of restrictions and / or framework conditions regarding the equipment used for production or the available infrastructure.

Chemical rules consider, for example, different chemical compositions of the products to be produced and the respective raw materials and supplies required for their production, it being ensured that a second product a previous first product without major financial and / or technical expenses, such as cleaning the for the preparation of the first product used, may follow. Accordingly, steels with a demanded very low carbon content, for example, must always be cast or produced before steels with a high carbon content in steelmaking, ie a sequence of the products or steels with increasing carbon content has to be considered. Furthermore, it must be ensured that successive product groups of the order-required specification can be produced at all. For example, the preparation process of some high-purity steels, the so-called "wash grades", prepares the process for a thorough cleaning of the equipment to be used for the production in order to remove impurities and / or residues of previous melts or steels.

Physical rules take into account, in particular, physical variables to be observed in relation to the production process, such as temperature, pressure and generally to be observed specifications and settings of the various resources used.

In a second step, the presorted list is separated into individual product families and, based on at least one preselectable product parameter, for example the quality and / or width, a grouping of the products to be produced into individual product groups is performed rule-based. In a third step, a mathematical model is created for each product group, depending on the characteristic size and rule-based. The mathematical model including the objective functions to be optimized, such as minimal downtime of the plant operation or a continuous production process or minimal committee, embedded in the MILP approach, contains all the information necessary to carry out a successful sequencing.

According to the method, either the constant and / or increase or the increase or the constant and / or the decrease or decrease of product characteristics within the product sequence of each product group is allowed or made possible.

The mathematical model has to satisfy the aforementioned flexibility.

Finally, in a fourth step, by applying common MILP solution methods to the mathematical model, optimized sequencing of the products within each product group, the product groups within each product family, and thus also the products within a product family, is accomplished and achieved.

The execution of the method according to the invention is preferably carried out by means of a system for optimized planning of complex production sequences in large-scale plant operations, in particular the steel and / or pulp and / or paper and / or chemical / pharmaceutical industry, which means for programmatic application of, on Methods and algorithms of Mixed Integer Linear Programming (MILP) based, mixed-integer optimization method, wherein means are provided, which are adapted to processing and / or inclusion or compliance with predetermined rules and product and equipment characteristics gradually optimized grouping and optimized To perform sequencing of products to be produced in product families and product groups and to determine an optimized product sequence or production sequence. A computer program which has the features of the method according to the invention and is implemented by suitable hardware, in particular a data processing device with input and display device and optionally with network and / or Internet connection and which optionally interacts with a data memory, leads to a preferred embodiment of the system according to the invention , A computer program, in particular a computer program stored on a data carrier, which has the features of the method according to the invention, is therefore expressly included in the disclosure content of the present application.

These and other advantageous embodiments and embodiments of the invention are the subject of the dependent claims.

Reference to an embodiment of the Erfindong shown in the accompanying figures, the invention, advantageous embodiments and particular advantages of the invention will be explained and described in detail.

Show it:

Fig. 1 Exemplary underlying steelmaking process

Fig. 2 exemplary procedure

Fig. 3 exemplary pre-sorting in sequences or product groups with the

Product characteristics Quality, width, thickness

Fig. 4 on the presorting of FIG. 3 based compatibility matrix Fig. 5 optimized grouping and sequencing of the products to be produced under the condition of exclusively decreasing widths within a sequence

Fig. 6 according to the invention optimized grouping and sequencing of the products to be produced

Fig. 7 overall arrangement with exemplified inventive

system

The further explanation of the invention is made by way of example based on the steel production process shown in Fig. 1 in a steel mill.

In the steel production process used here as an example, two electrically powered arc furnaces 01 and O2 are used as blast furnaces, which are operated alternately and in which molten, as-new steel is combined with scrap iron or scrap or mixed. In addition, for the metallurgical treatment of the melt an argon-oxygen Dekarburierungseinheit D1 to reduce the carbon content of the melt, the so-called. "Freshen", as well as for monitoring and control of the chemical composition and temperature of the melt, a ladle with metallurgical devices G1, for example, a so-called "Converter", used. The final casting of the liquid steel is carried out by means of modern continuous casting in a continuous casting S1, which ensure a constant solidification and an optimal microstructure of the slabs (steel blanks) and or round rods produced. A continuous casting process usually comprises between 8-10 furnace fillings. Once these have been completed, regular maintenance and / or maintenance work will be carried out on the continuous caster. The maintenance cycle is thus at about 8-10 finished Ofenbefüllungen or melts. Steelmaking is an extremely time-critical process with a comparatively high energy requirement, in which planning decisions concerning the course of the steelmaking process are generally still manual, that is to say made by an expert, which is especially true for highly complex process flows and a large number of considering the underlying conditions as difficult to almost impossible.

In particular, the last processing step, namely the continuous casting of the melt in order slabs and / or round steels is here due to the variety to be considered and fulfilled rules and / or frameworks to achieve the required steel quality as the planning technically most difficult to implement process.

The aforementioned rules essentially include geometric, chemical and / or physical rules and / or requirements. However, resource-specific rules and / or parameters may also be considered. These include, by themselves or in combination, for example, availability, condition, throughput, consumption, achievable quality and / or production speed, utilization, capacity dependencies and / or links, operating, standstill and / or maintenance information and times of resources. Also product and / or process paths and times, in particular also run or cycle times can be advantageously included

In this case, geometric rules are largely based on restrictions and / or framework conditions with regard to the equipment used for the production or the available infrastructure, so it is assumed, in particular in known methods, that the casting process in steel production takes place only in the sequence of decreasing width or width the molds and / or products is feasible. Chemical rules, for example, take into account the educts and / or admixtures required for the production of different steels, both

• ensure that the next melt of the previous ones can follow without major expenditures, such as ladle cleaning, for example, products or steels with a demanded very low carbon content should always be poured in front of products with a higher carbon content, ie a sequence of products resp Steels with increasing carbon content should be considered as well

• it must be ensured that successive product groups of the required specification can be produced at all, for example some high-purity steels and / or stainless steels, the so-called "wash grades", require thorough cleaning of the equipment to be used, for example impurities and residues of preceding melts, before the start of the production process or steels and / or castings.

Physical rules in this case relate in particular to temperatures to be maintained, for example, the furnaces, the melt and / or critical temperatures of the equipment used, as well as generally to be observed specifications and settings of the various resources used. For example, the change in thickness of cast slabs or slabs is a time-dependent process that should be avoided, if possible.The equipment used also has limitations, so the caster, the "caster", tolerates only 8 furnace fillings ("heats ") or melting batches before extensive maintenance must be performed.

For example, the rules mentioned above must be observed or applied between two successive batches of melt and their underlying product groupings, as well as at each sequence change. Within a sequence, which usually comprises 8 to 10 melt batches and / or Ofenbefüllungen, a continuous, uninterrupted casting process is possible., A sequence change, however requires the implementation of maintenance and or maintenance measures, so that the production or the continuous casting process must be interrupted. Accordingly, one seeks to achieve the longest possible casting sequences to reduce the downtime of the plant operation or production losses and thus to increase the efficiency of the plant operation or manufacturing process. But no longer than the required maintenance interval.

Interruptions of the continuous casting process occur, for example, if for the order production of various products, especially steel blanks, for example, different geometrical dimensions conversions of resources, here the continuous casting required.

In order to minimize plant downtime, in this case the continuous casting plant, and to make a continuous production process as efficient as possible over the longest possible period of time makes an optimized planning of the product sequence indispensable.

As shown in FIG. 2, this is done in a first step S1, depending on order stock information and the product characteristics 2 contained, such as delivery date, width, quality, grade and thickness of the respective product, as well as by predetermined rules, which are co-determined in particular by the manufacturing process and / or the existing resources, a sequential pre-sorting of the products to be produced

1. after due date

2. by far

3. after quality

4. by grade and / or chemical composition

5. by thickness and the like, wherein any characteristics and factors that can take influence on the respective production sequence and / or process sequence, in particular the casting process, can be included or processed.

The aforementioned rules essentially take into account geometric, chemical and / or physical requirements and / or limitations of the steelmaking process and / or the continuous casting plant used for product production and / or status, performance and / or operating information of the existing resources.

In a second step 4, the sequentially presorted list of the products to be produced is subdivided into individual product families, with all products of the same thickness and quality being able to form one product family in each case. Within each product family, it is advantageously possible, based on at least one preselectable product parameter, in particular the quality and / or width, to regularly group the products to be produced into individual product groups, wherein no more than 8 products should be contained within a product group.

If the casting sequences, that is, the number of melts or furnace fillings required, are not already predetermined by a CPM (Corporate Performance Management) system, for example, they can be determined using the specified method. A restriction of the degrees of freedom, in particular by specifying the number of furnace loads, allows a more efficient optimization so that a specification of both an upper and a lower limit, in particular as a further characteristic or rule, appears advantageous. The upper limit value can be taken directly from the presorting, wherein the lower limit value can be estimated theoretically.

With regard to the quality requirement, it should be noted that there are numerous products which are subject to a very high purity requirement, for example, contaminants. conditions with nickel. Of particular importance are such considerations, especially in the pharmaceutical and / or chemical industry. Products or product groups in which a certain degree of purity or composition and / or a certain quality of importance are usually produced on or in succession to so-called "wash grades", wherein the way of dealing with such requirements and / or products separately The easiest way to deal with this is to produce such qualities in a sequence or sequence immediately following the respectively corresponding "wash-grades" (German term?).

In a third step 6, a mathematical model and, as a preliminary stage of the mathematical model, first of all a compatibility matrix is created for each product group, which represents the complex and / or non-linear rules underlying the mixed-integer optimization method and maps all possible product pairings accordingly , Mainly chemical rules and parameters are considered and included. The matrix elements can assume the values 0 or 1 here. The matrix element P ₁ , - has the value 1 if product / can be prepared by product /. If this is not the case, the matrix element P _{u has} the value 0. Advantageously, these compatibility information can also be stored in a suitably prepared database, a flat-file (hierarchical data structure) or a program memory, for example also in tabular form, for further processing and provided. The mathematical model together with the objective functions to be optimized and / or their coefficients, for example minimum downtimes of the plant operation or a continuous production process, embedded in the MILP approach, provide all the information necessary for carrying out a successful sequencing or meet all the requirements for the Carrying out a successful sequencing.

Accordingly, an optimized product or production sequence is first determined within each product family. It is also advantageously possible to carry out the optimization only over partial areas, for example in the case of not exactly known (fuzzy) process parameters and / or resource information, an optimization for all production sequences (German expression) or for only a smaller part of the production sequences, in particular casting sequences, with complete parameter set and / or resource information.

An optimization of only a part of the product sequences or individual sequences only makes sense if the individual results are also usable in a combined manner, which is advantageously achievable by linking the individual production sequences or product sequences in a further step and / or placing them in relation. In order to avoid conflicts and shorten waiting times, this may also lead to a redistribution or adaptation of the respectively available resources, in particular of the resources, or may necessitate such.

Moreover, at least in the field of steelmaking and / or processing (steel industry), either the constant and / or increasing or staying constant and / or decreasing or decreasing, for example, the width within the product sequence of each product group is allowed ,

The mathematical model has to satisfy the aforementioned flexibility and can be stated as follows:

To describe the dependencies, four cases C1, C2, C3 and C4 are to be distinguished:

Ch P ₁ , = 1, w, ≤ w ,,, t, ≤ t,

Ql-P _n , = 1, w ,, ≦ w "t, ≦ t,

C3: P ,, = 1, w ,, ≦ w "t, ≦ t,

CA: P ₁ , = 1, w, ≦ w ,,, t, ≦ t " where w indicates the width of the respective product and t indicates a type number describing the quality of the respective product. As a rule, it should be noted that the product with the type number 1, ie with higher quality, must always be cast or produced before the product with type number 2, ie with lower quality.

Let Z ₉ be a binary variable that takes the value 1 if a sequence g is used, that is, contains at least the product, otherwise it has the value 0. The goal is to minimize the total number of sequences or product groups. Expressed by the following relation R1

min z _g (R1) geG

G gives an estimate of the maximum required number of groups.

The assignment of products i to product groups g is carried out by the binary variable Xj ₉ . Each product i must be uniquely assigned to exactly one product group g, as indicated by objective function or relation R2, whereby an upper limit Mmax, for which the maximum number of products in a product group is to be adhered to, is illustrated by relation R3. The variables for unused product groups have the value 0. Here, I describe the quantity of the products to be produced.

Σ * _β = 1 Vi e / (R2) geG

Σx _lg ≤ M _max ^ z _g Vg e G (R3)

ocg is a binary variable with the value 1 if within the product group or sequence g the product width w increases. qi _g is a variable that serves to soften or defuse some of the specified target functions for the last product in a sequence. For a product sequence within a product group of increasing width (α = 1), for all products except the last product of the sequence, there must be a suitable subsequent product expressed by Relation R4. objective function or relation R5 indicates the corresponding case with decreasing width (α = 0) within a product sequence.

»'E / P (R4)

Vi e /, Vg e G

* _« - ^ _« ^≤ Σ ^x r _g + M _max -a _g

'e / | C2 (R5)

Corresponding to the two aforementioned objective functions or relations R4 and R5. describe the two subsequent objective functions, R6 for increasing distances and R7 for decreasing distances within a sequence, the case in which all products, except the first product, within a product sequence of a product group or a sequence must have a suitable preceding product. The objective function for the first product of a sequence is attenuated by the variable n _g .

^X ' _g ' ^r 'g ^≤ Σ ^X ' g ^{+ M} max G - ^a g)

'We 3 (R6)

V / e /, Vg e G

Since the sequence of products within a product group can not be controlled directly, two further target functions R8 and R9 are required to rule out errors or incompatibilities: The target function R8 prevents the occurrence of products with a larger width and with a smaller type number, ie higher quality, as well as products with a smaller width and with a higher type number, ie lower quality, for increasing or increasing distances within a sequence or a product sequence of a product group. The second objective function or relation R9 describes the corresponding case for decreasing distances within a sequence. It should be noted here notes that in the case of pre-sorting of the products depending on the quality in index comparison is sufficient. + Σ ^x _* fc - ^M _ma χ0 - <x _g ) ≤

/'e/|w,.<w,, ', <', ■ (R8)

The relations R10 and R11 allow exactly two exceptions per group, namely for the first and the last product of a sequence.

Σq, _g ≤ z _g Vg € G (R10)

/ E /

Σr _lg ≦ z _g Vg € G (R11)

/ E /

The ^' further objective functions or relations serve to further delimit the search space or to compact the model. The flag for increasing widths within a sequence is set to 0 for nonexistent sequences, see relation R12. The product groups are ordered according to the number of products contained in them, see relation R13. In addition, equation R14 causes the active groups to be prepended. The number of imageable groups | G |, is achieved by presorting. It is common for some of these relations to appear redundant after optimization.

Vg e G (R12) ≤0 Vg e G (R13)

, <o Vg e G (R14)

The exception variables for the first and last product of a sequence are real variables in the range between 0 and 1. z _g , x _lg , a _g e {0,1} O ≤ q _ls! , r <\

Finally, in a fourth step, by applying common MILP solution methods to the compatibility matrix or mathematical model and solving the model given by the aforementioned objective functions, optimized sequencing of the products within each product group, the product groups within each product family and thus also within the products reached a product family.

FIG. 3 shows an exemplary presorting in sequences or product groups with the product parameters quality, width, thickness. After presorting, there are 5 sequences separated by thicker horizontal lines. The prerequisite for this is that products of different quality must be produced in the order of 101A → 101B-> 101C → 101, and the maximum width change between two consecutive products may be 7.0 units.

FIG. 4 shows a compatibility matrix based on the presorting according to FIG. 3

FIG. 5 shows an optimized grouping and sequencing of the products to be produced, assuming only decreasing widths within a sequence, based on FIGS. 3 and 4.

FIG. 6 shows an optimized grouping and sequencing of the products to be produced according to FIG. 3 and FIG. 4.

Furthermore, FIG. 7 shows an overall concept or overall arrangement for a large-scale plant operation from the steel industry with several components and The inclusion of an exemplary trained system for the optimized planning of complex production sequences in large-scale plant operations shown, where systemically in interaction

• with an ERP (Enterprise Resource Planning) component 12 for resource planning and / or administration, job information to a CPM (Collaborative Production Management) component, ie a component for analysis and reporting but also for planning and forecasting, and / or an MES (Manufacturing Execution System), that is a component for production management with direct connection to the respective automation system and / or real-time production control and data acquisition, can be transmitted,

• Products with matching or corresponding product specifications can be determined by means of the CPM component 14 and the extent of the melting or casting process and in particular the number of slabs or ingots can be determined on the basis of the correspondences determined,

• by means of the CPM component 12, the current process status and / or the information contained in the mathematical model, in particular the objective functions and / or their coefficients, can be determined or interrogated, and

• by means of the CPM component 14 required and / or essential information 15 for performing an optimized planning complex production sequences, such as process information 15a, order backlog, configuration and / or contents of the mathematical model 15c, maintenance and / or status information of existing resources 15b on an exemplified system 16 for the optimized planning of complex production sequences in large-scale plant operations can be transmitted, and wherein

• By means of the aforementioned system 16 and the information transmitted while processing and / or incorporating predetermined rules and product parameters, in particular also target specifications and resource characteristics corresponding optimization model (mathematical model) can be created and, in particular by means of a processing component in the form of a model solver 18 by application of the respective solution algorithm, the respective optimization model (mathematical model) solvable and optimized grouping and optimized sequencing of products to be produced in product families and product groups feasible and optimized Product sequence or production sequence can be determined,

• all relevant information and / or the determined optimized product sequence or production sequence in a log or report, in particular a log file 20 on a data storage, are detectable, and

• and the determined, optimized product or production sequence for the conversion and adaptation of the respective production process to the respective CPM / MES 12 is transferable or can be transferred back.

The information underlying the optimization and thus the optimized production plan production can thereby be transmitted by means of XML or other known data structures-either file-based or memory-based, also via corresponding communication links and / or data carriers.

The optimization request or the corresponding request to the system and / or the initiation of the optimization process is effected by a corresponding "hosting system", in particular a CPM system or a corresponding Kkomponente, which all relevant information to the optimization process or the system producing an optimized production plan transmitted.

Claims

claims

1. A method for the optimized planning of complex production sequences in large-scale plant operations, in particular the steel industry, by means of programmatic application based on methods and algorithms of the MIXED INTEGER Linear Programming (MILP), mixed-integer optimization method, wherein processing and / or incorporation of predetermined rules and product characteristics as well as equipment characteristics, an optimized grouping and optimized sequencing of products to be produced in product families and product groups is carried out step by step and an optimized product sequence or production sequence is determined.

2. The method according to claim 1, characterized in that

• in a first step (2) product-dependent and resource-dependent and rule-based sequential presorting of products to be produced according to products is carried out,

In a second step (4), the presorting is subdivided into individual product families depending on characteristics and / or rules, and a grouping of the products to be produced into individual product groups is carried out within each product family on the basis of at least one product parameter and at least one resource parameter.

• In a third step (6), a mathematical model is created for all product groups for each product group, depending on the product, the operating resource and the rule

In a fourth step (8), by applying common MILP solution methods to the mathematical model, optimized sequencing of the products within each product group, the product groups within a product family as well as the products within a product family and / or the products to the respective equipment is performed and is achieved.

3. The method according to any one of claims 1 or 2, characterized in that an optimized grouping and Sequenzzierung products to be produced in product groups is achieved by reaching for relevant product parameters either the same and / or increasing or increasing or the same and / or decreasing or decreasing values become.

4. The method according to any one of the preceding claims, characterized in that automated and / or manual weighting of the various product parameters and / or resource characteristics are performed.

5. The method according to claim 4, characterized in that based on the weights of the individual product characteristics a product characteristics ranking is created.

6. The method according to any one of the preceding claims, characterized in that the predetermined rules and / or the weightings of the various product parameters by the respective plant operation and / or the respective manufacturing process co-determined or coined.

7. The method according to any one of the preceding claims, characterized in that weightings of the various product parameters are taken into account in the predetermined rules.

8. The method according to any one of claims 2 to 7, characterized in that the sequential pre-sorting is performed based on weighted product characteristics and / or resource characteristics.

9. The method according to any one of the preceding claims, characterized in that in each case both the rise and the fall of product characteristics within the product sequence of each product group allowed or enabled.

10. The method according to any one of the preceding claims, characterized in that as a resource characteristic resource state information and / or loading and / or - linkages and / or objectives or target functions and / or processing and utilization times and / or maintenance times and / or maintenance cycles are used and / or recycled.

11. System for the optimized planning of complex production sequences in large-scale plant operations, in particular in the steel industry, with means for the program-specific application of mixed integer linear programming (MILP) based methods and algorithms using mixed-numbered optimization methods, with means being provided therefor processing and / or incorporating predetermined rules and product characteristics as well as resource characteristics, to carry out an optimized grouping and optimized sequencing of products to be produced in product families and product groups step by step and to determine an optimized product sequence or production sequence.

12. System according to claim 11, characterized in that the resource parameter is resource state information and / or equipment power and / or resource dependencies and / or links and / or targets or target functions and / or processing and utilization times and / or maintenance times and / or maintenance cycles used and / or used.

13. System according to claim 11 or 12, characterized in that

• means are provided with which product and resource parameter-dependent and rule-based sequential pre-sorting of products to be manufactured according to product families is feasible,

• Within each product family, a grouping of the products to be produced into individual product groups can be carried out on the basis of at least one product parameter and resource parameter, based on rules.

• a mathematical model can be determined for each product group as a function of product and resource characteristics and rule-based; and • Means are provided by means of which the mathematical model can be used to achieve and achieve optimized sequencing of the products within each product group, the product groups within a product family as well as the products within a product family by using common MILP solution methods.

14. System according to any one of claims 11 to 13, characterized in that means are provided with which an optimized grouping and Sequenzzie- tion products to be produced in product groups can be carried out by relevant product parameters either the same and / or increasing or increasing or the same and / or decreasing or decreasing values are achievable.

15. System according to one of the preceding claims 11 to 14, characterized in that automated and / or manual weighting of the various product parameters and / or1 resource characteristics are feasible.

16. System according to claim 15, characterized in that based on the weights of the individual product parameters a product characteristics ranking can be created.

17. System according to any one of the preceding claims 11 to 16, characterized in that the predetermined rules and / or the weightings of the various product parameters by the respective plant operation and / or the respective manufacturing process mitbestimmt or are coined.

18. System according to any one of the preceding claims 11 to 17, characterized in that are taken into account in the predetermined rules weights of the various product parameters.

19. System according to one of claims 11 to 18, characterized in that the sequential pre-sorting based on weighted product characteristics and / or resource characteristics is feasible.

20. System according to any one of the preceding claims 11 to 19, characterized in that in each case both the rise and the fall of product characteristics within the product sequence of each product group allowed or enabled.

21. System according to any one of the preceding claims 11 to 20, characterized in that as a resource characteristic resource state information and / or resources power and / or resource dependencies and / or links and / or objectives or target functions and / or processing and utilization times and / or maintenance times and / or maintenance cycles are used and / or recycled.